Побудова динамічних факторних моделей для прогнозування розвитку економічних систем

Olga Katunina

doi:10.33987/vsed.1(69).2019.118-127

Authors

Olga Katunina Kyiv National Economic University named after Vadym Hetman, Ukraine https://orcid.org/0000-0001-7584-0037

DOI:

https://doi.org/10.33987/vsed.1(69).2019.118-127

Keywords:

econometrics, forecasting, physical economic, dynamic factor models, time series, dynamic factor analysis

Abstract

The simulation of dynamic economic systems whose evolution is described by a system of observable variables is considered in the article. Methodology of dynamic factor modeling was used; mathematical model that combines approaches of classical factor and autoregressive analysis was built. It has been established that the systems of dynamic factors describe the general dynamics of the selected group of economic indicators. An algorithm for constructing a dynamic model, in which dynamic factors are determined sequentially in solving special problems of nonlinear programming, is proposed. The first factor describes the movement of entire system as a whole and characterizes the general trend, since a linear combination of original time series is used to find it. Other factors, which built on the basis of residual series take into account the deviations of individual indicators from their regression estimates and describe fluctuations of time series. The main calculated relationships of the constructed model of dynamic factor analysis are given. For estimate the prediction error, the ex-post forecast method was used. Directions for investigating of the forecast quality by the number of factors taken into account, the lag length, and considered nonlinear programming problems parameters are proposed. It was determined that the choice of these parameters in the constructed algorithm allows minimizing the prediction error for a specific time series and obtaining several possible options for the system development. The developed model of dynamic factor analysis can have a wide practical use, because it opens the possibility to evaluate the impact of forcing a change in the predicted values of one or several indicators on the entire system dynamics. The directions for constructing a controlled multidimensional forecasting model for evolution analyzing of economic dynamic systems of various natures are substantiated. Obtaining a multivariate forecast of economic systems evolution is particularly important in strategic planning both at the macroeconomic level and for individual industries and enterprises. The proposed method of dynamic factor analysis of time series systems has certain universality and, together with other econometric methods, can be used, for example, in ecology, medicine, physics and other fields of science.

Author Biography

Olga Katunina, Kyiv National Economic University named after Vadym Hetman

PhD in Economics, Associate Professor, Department of Economics and Mathematical Modeling

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